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Limn: Using Image and Video Technology for Visualizing a Million Cases of Multivariate data. Di Cook, Les Miller, Manuel Suarez, Peter Sutherland, Jing Zhang. History. John McDonald’s 3D rotation and linked brushing in early 90s. Why Scale Visual Methods?.

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Limn using image and video technology for visualizing a million cases of multivariate data

Limn: Using Image and Video Technology for Visualizing a Million Cases of Multivariate data

Di Cook, Les Miller,

Manuel Suarez,

Peter Sutherland, Jing Zhang


History
History a Million Cases of Multivariate data

John McDonald’s 3D rotation and linked brushing in early 90s


Why scale visual methods
Why Scale Visual Methods? a Million Cases of Multivariate data

All three data sets have correlation

approximately 0.7


Type of data
Type of Data a Million Cases of Multivariate data

Real-valued multivariate,

spatio-temporal context, class information


Goals
Goals a Million Cases of Multivariate data

  • Provide multiple scatterplot displays, either as several static plots, or a sequence of tour projections.

  • Link brush between them in real-time.

For 100Gb of multivariate data:


Real time graphics
Real-time Graphics a Million Cases of Multivariate data

GGobi can handle 1 million points, but…

  • There is a lot of overplotting even when using pixel sized glyph.

  • Brush slow to color with continuous updating.

  • Tour is too slow to tolerate: use scramble


Problems with large data sets
Problems with Large Data Sets a Million Cases of Multivariate data

  • Data Reduction: MV binning produces visual artifacts, screen size induces a binning, though.

  • Scaling of Methods: computation, storage, memory.


Screen resolution
Screen Resolution a Million Cases of Multivariate data

  • Limited screen space induces binning

  • Alpha-blending removes focus from low density pixels

  • Using grey scale


Indexing projections
Indexing Projections a Million Cases of Multivariate data

nxp data matrix

Pixel resolution plot window


Limn software
Limn Software a Million Cases of Multivariate data

Two Steps:

  • Create indexing on projected data, or an animation sequence and save as QuickTime movie.

  • View density plots or animation, and interact with it by brushing, and overlaying subsets of data.

* Code is written in Java


Data description
Data Description a Million Cases of Multivariate data

Seasonal metrics data computed on AVHRR images across the USA in 1989: SoST, SoSN, EoST,EoSN, MaxT, MaxN, TotalNDVI.

And land cover classes: agriculture, grassland, deciduous, evergreen, barren.


Limn using image and video technology for visualizing a million cases of multivariate data
Demo a Million Cases of Multivariate data

  • Scatterplot matrix

  • Tour movie


Currently we re also exploring
Currently we’re also exploring… a Million Cases of Multivariate data

  • Sampling distributions of the pixel population.

  • Overlaying movies for working with larger data.

  • Broader array of data parsers.


Contact information
Contact Information a Million Cases of Multivariate data

Software is archived at: www.sourceforge.net

Email: dicook@iastate.edu